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Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data which are becoming difficult to manage. Identifying the desired featured chemical with the desired biological activity from millions of chemicals is a challenging task.

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This page is a summary of: A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction, Indian Journal of Pharmacology, January 2018, Medknow,
DOI: 10.4103/ijp.ijp_304_17.
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